An expert-driven digital platform for decision support in sustainable building retrofitting
• Developed an expert-driven digital platform for sustainable building retrofit decision-making. • Supports both global and property-specific configurations with adaptable decision criteria. • Integrates a structured three-step decision-making workflow. • Combines subjective and objective weighting with hybrid analysis for transparent rankings. • Validated through a mid-terrace case study using expert input and location-specific environmental data. This study introduces an expert-guided decision-support platform developed to improve the selection of building retrofit measures for energy efficiency. The platform addresses a key gap in existing tools by combining expert input with systematic decision logic, offering a more transparent and adaptable approach to retrofit planning. Unlike simulation-based or policy-orientated systems, this platform focuses on supporting real-world decisions at the property level. It allows for both general (global) and building-specific configurations, giving users the flexibility to define and adjust decision criteria based on retrofit needs. A three-phase analytical workflow supports users via assigning expert importance, classifying assessment criteria, and deciding on a ranking method. The strategy combines data-driven and expert-based weighing methodologies, resulting in balanced and context-aware outputs. The system includes an explainable AI module that generates editable reasons for final recommendations, allowing stakeholders to better understand and discuss decisions. The platform’s efficacy was demonstrated through a case study of a mid-terrace house, showing strong potential for supporting consistent, stakeholder-informed, and auditable retrofit decisions. This work contributes a flexible and scalable solution of practical value to planners, housing authorities, and retrofit consultants.
Authors
- Hafiz Muhammad Athar Farid (ORCID: https://orcid.org/0000-0002-8318-0750)
- Vladimir Šimić (ORCID: https://orcid.org/0000-0001-5709-3744)
- Richard Hill (ORCID: https://orcid.org/0000-0003-0105-7730)
- Hafiz Muhammad Shakeel (ORCID: https://orcid.org/0000-0003-2307-2763)
- Shamaila Iram (ORCID: https://orcid.org/0000-0003-0217-500X)
Institutions
- Doğuş University (TR)
- University of Huddersfield (GB)
- Széchenyi István University (HU)
- Leeds Beckett University (GB)
- Yuan Ze University (TW)
Publication Details
- Journal
- Energy and Buildings
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1016/j.enbuild.2025.116770
- Citations
- 1
- Primary Topic
- Building Energy and Comfort Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.01